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Research Associate (Computer Engineering/Computer Science/Electronics Engineering)

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NANYANG TECHNOLOGICAL UNIVERSITY logoNanyang Technological University · Nanyang Technological University, Singapore
S$48K–S$96K/yrContractUnknownToday
3D PrintingComputer VisionDeep LearningDocumentationMachine LearningPyTorch
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Responsibilities

  • Conduct research on advanced AI algorithms for processing and modeling high‑dimensional datasets, including tensor‑based and multi‑modal data.
  • Collaborate with researchers and PhD candidates to design and develop AI applications in image processing, computational imaging, and computer vision.
  • Review and analyze recent research papers and baseline implementations; participate in regular discussions and provide weekly updates to the advisor and team.
  • Prepare, write, and publish research findings in top‑tier journals and international conferences.
  • Contribute to the preparation of research proposals, project documentation, and progress reports.
  • Job Requirements:
  • Master's degree in Computer Engineering, Computer Science, Electronics Engineering, or equivalent, with at least 2 years+ of research experience.
  • Proficiency in deep learning frameworks such as Pytorch
  • Independent, highly analytical, proactive and a team player
  • Excellent teamwork and verbal, written communication skills
  • Proven track record of publications in leading Journals and conferences within the relevant fields, supported by strong mathematical expertise
  • Kindly note that only shortlisted candidates will be notified.

Additional Information

Hyundai-NTU-A*STAR Corporate Lab offers an excellent R&D environment to create novel technologies with the world leading automotive company, Hyundai by translating the research into the dark factory directly with implementing and validating the research using AI, Robotics, 3D Printing and Digital Twins. Artificial Intelligence (AI) related fields, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems, which can benefit a wide range of real-world applications.


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